Question

1. The correlation for a set of data is r=0.99. The residuals plot for that set of data shows a curved pattern, like a "U" shape. What conclusion about the data do you reach based on this information?

A. The association between the explanatory and response variables is strong, positive and linear.

B. It is not appropriate to use a linear regression model as the scatterplot is curved.

C. The association between the explanatory and response variables is strong, positive and curved.

D. It is not appropriate to look at the residuals plot because the correlation shows the data have a strong linear association.

Answer 1

Ans:

It is not appropriate to use a linear regression model,as residual plot have a pattern,residual plot should have random pattern for a good fit.

A residual plot is a graph that shows the residuals on the vertical axis and the independent variable on the horizontal axis. If the points in a residual plot are randomly dispersed around the horizontal axis, a linear regression model is appropriate for the data; otherwise, a non-linear model is more appropriate.